This post helps you with loading your data from QuickBooks to PostgreSQL. If you are looking to get analytics-ready data without the manual hassle, you can integrate QuickBooks to PostgreSQL with RudderStack, so you can focus on what matters, getting value out of your financial data.
Access your data on QuickBooks
The first step in loading your QuickBooks data into any data warehouse solution, is to access the data and start extracting it through the available web API.
QuickBooks has a very rich and well-defined API, reflecting the extensive development that the product has gone through. The API is designed around the following main groups of resources.
- Transaction resources.
- Name list resources.
- Report resources.
- Supporting resources.
Report resources, contain all the reports that QuickBooks also offer from within the application. They have a different data model than the rest of the resources, and you need to account for these differences when extracting data from the API.
The rest of the resources contain pretty much every possible entity that QuickBooks define, each one with a different data model that is serialized in JSON.
In addition to the above, the things that you have to keep in mind when dealing with any API like the one Quickbooks has are:
- Rate limits. Every API, has some rate limits that you have to respect.
- Authentication. You authenticate on QuickBooks using an API key.
- Paging and dealing with big amount of data. Platforms like QuickBooks tend to generate a lot of data, as financial transactions and accounting involve many different events that can happen. Pulling big volumes of data out of an API might be difficult, especially when you consider and respect any rate limits that the API has.
QuickBooks is an accounting software released and maintained by Intuit. It currently has two versions, a desktop one and a cloud-based one. This guide is about the latter, where data can be accessed through the REST API that Intuit has built around the product.
QuickBooks is mainly used by small and medium-sized companies and covers the whole spectrum of accounting-related activities of a company, from payroll to the management and payment of bills.
Historically, QuickBooks is one of the first accounting software that was ever released, its initial release was for the DOS operating system and it managed to dominate the small and medium sized companies market for many years.
Transform and prepare your QuickBooks data for PostgreSQL
After you have accessed your data on QuickBooks, you will have to transform it based on two main factors,
- The limitations of the database that the data will be loaded onto
- The type of analysis that you plan to perform
Each system has specific limitations on the data types and data structures that it supports. If for example, you want to push data into Google BigQuery, then you can send nested data like JSON directly. But when you are dealing with tabular data stores, like Microsoft SQL Server, this is not an option. Instead, you will have to flatten out your data before loading it into the database.
Also, you have to choose the right data types. Again, depending on the system that you will send the data to and data types that the API exposes to you, you will have to make the right choices. These choices are important because they can limit the expressivity of your queries and limit your analysts on what they can do directly out of the database.
QuickBooks has a very rich data model, where many of the resources that you can access might have to be flatten out and be pushed in more than one tables.
Also, QuickBooks has a special set of resources, the reports, that have a tabular but nested format that looks similar to a complex spreadsheet. In order to make these reports compatible with a database data model, you need to redesign, parse and transform the reports into a tabular form that can be stored into a database.
Each table is a collection of columns with a predefined data type like an integer or VARCHAR. PostgreSQL, like any other SQL database supports a wide range of different data types.
A typical strategy for loading data from Quickbooks to a Postgres database is to create a schema where you will map each API endpoint to a table. Each key inside the Quickbooks API endpoint response should be mapped to a column of that table and you should ensure the right conversion to a Postgres compatible data type.
Load data from Quickbooks to PostgreSQL
For example, if an endpoint from Quickbooks returns a value as String, you should convert it into a VARCHAR with a predefined max size or TEXT data type. tables can then be created on your database using the CREATE SQL statement.
Once you have defined your schema and you have created your tables with the proper data types, you can start loading data into your database.
The preferred way of adding larger datasets into a PostgreSQL database is by using the COPY command. COPY is copying data from a file on a file system that is accessible by the Postgres instance. In this way, much larger datasets can be inserted into the database in less time. COPY requires physical access to a file system in order to load data.
Nowadays, with the cloud-based, fully managed databases, getting direct access to a file system is not always possible. If this is the case and you cannot use a COPY statement, then another option is to use PREPARE together with INSERT, to end up with optimized and more performant INSERT queries.
Updating your Quickbooks data on PostgreSQL
As you will be generating more data on Quickbooks, you will need to update your older data on PostgreSQL. This includes new records together with updates to older records that for any reason have been updated on Quickbooks.
You will need to periodically check Quickbooks for new data and repeat the process that has been described previously while updating your currently available data if needed. Updating an already existing row on a PostgreSQL table is achieved by creating UPDATE statements.
Another issue that you need to take care of is the identification and removal of any duplicate records on your database. Either because Quickbooks does not have a mechanism to identify new and updated records or because of errors on your data pipelines, duplicate records might be introduced to your database.
In general, ensuring the quality of the data that is inserted in your database is a big and difficult issue and PostgreSQL features like TRANSACTIONS can help tremendously, although they do not solve the problem in the general case.
The best way to load data from QuickBooks to PostgreSQL
So far we just scraped the surface of what you can do with PostgreSQL and how to load data into it. Things can get even more complicated if you want to integrate data coming from different sources.
Are you striving to achieve results right now?
Instead of writing, hosting, and maintaining a flexible data infrastructure use RudderStack that can handle everything automatically for you.
RudderStack with one click integrates with sources or services, creates analytics-ready data, and syncs your QuickBooks to PostgreSQL right away.
Sign Up For Free And Start Sending Data
Test out our event stream, ELT, and reverse-ETL pipelines. Use our HTTP source to send data in less than 5 minutes, or install one of our 12 SDKs in your website or app.